面向特征识别和变化检测的多光谱卫星图像分析VAST挑战赛2017:单幅图像分析便捷性优秀奖

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI:10.1109/VAST.2017.8585482

S. Malla, Anwesh Tuladhar, Ghulam Jilani Quadri, P. Rosen

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引用次数: 1

摘要

卫星图像对地物遥感很有帮助。然而，这种多光谱图像不能用现成的成像工具显示。我们在处理中开发了一个工具，它能够读取多光谱图像并将每个波段显示为灰度图像。该工具还允许将任何波段映射到显示图像的红色，绿色或蓝色通道。在本文中，我们描述了如何使用这种工具来识别土地特征，并协助发现随时间的变化。我们使用我们的工具成功解决了VAST挑战2017迷你挑战3。

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Multi-Spectral Satellite Image Analysis for Feature Identification and Change Detection VAST Challenge 2017: Honorable Mention for Good Facilitation of Single Image Analysis

Satellite images are helpful in remote sensing of land features. However, such multi-spectral images cannot be displayed using readily available imaging tools. We developed a tool in Processing that is able to read in multi-spectral images and display each band as a grayscale image. This tool also allows for mapping of any of the bands to red, green or blue channel of the displayed image. In this paper, we describe how such tool can be used in identifying land features as well as assist in finding changes over time. We used our tool to successfully solve the VAST challenge 2017 mini-challenge 3.

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2017 IEEE Conference on Visual Analytics Science and Technology (VAST)

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